Create app.py

app.py

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+import gradio as gr
+import tensorflow as tf
+from transformers import pipeline
+from huggingface_hub import from_pretrained_keras
+import numpy as np
+from keras.preprocessing.sequence import pad_sequences
+from keras.datasets import imdb
+
+# טעינת המודל מ-Hugging Face Hub
+try:
+    model = from_pretrained_keras("GiladtheFixer/Sentiment_Analysis")
+    print("Model loaded successfully!")
+except Exception as e:
+    print(f"Error loading model: {e}")
+
+# קבלת אינדקס המילים של IMDB
+word_index = imdb.get_word_index()
+
+def preprocess_text(text):
+    # המרה למילים
+    words = text.lower().split()
+    
+    # המרה למספרים
+    sequence = [word_index.get(word, 0) for word in words]
+    
+    # יצירת וקטור one-hot בגודל 10000
+    vector = np.zeros((1, 10000))
+    for num in sequence:
+        if num < 10000:  # מתעלם ממילים שהאינדקס שלהן גדול מ-10000
+            vector[0, num] = 1.
+            
+    return vector
+
+def predict_sentiment(text):
+    try:
+        # עיבוד הטקסט
+        processed_text = preprocess_text(text)
+        
+        # חיזוי
+        prediction = model.predict(processed_text)[0][0]
+        
+        sentiment = "Positive" if prediction > 0.5 else "Negative"
+        confidence = float(prediction if prediction > 0.5 else 1 - prediction)
+        
+        return {
+            "Sentiment": sentiment,
+            "Confidence": f"{confidence:.2%}"
+        }
+    except Exception as e:
+        return {
+            "Error": str(e)
+        }
+
+# יצירת ממשק Gradio
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs=[
+        gr.Textbox(label="Enter text to analyze", lines=4, placeholder="Type your text here...")
+    ],
+    outputs=gr.JSON(label="Prediction Results"),
+    title="Sentiment Analysis",
+    description="Enter any text to analyze its sentiment. The model will predict whether the text is positive or negative.",
+    examples=[
+        ["This movie was absolutely fantastic! I loved every minute of it."],
+        ["The service was terrible and the food was cold."],
+        ["It was okay, nothing special but not bad either."]
+    ],
+    theme=gr.themes.Soft()
+)
+
+# הפעלת הממשק
+if __name__ == "__main__":
+    iface.launch(share=True)  # שנה ל-share=False אם אתה לא רוצה לייצר קישור ציבורי